Regression analysis is a statistical tool used for the examination of relationships between variables. Linear regression analysis is used to estimate the strength and the direction of the relationship between two linearly related variables.

Explain the differences between the regression model, the regression equation, and the estimated-regression equation. Discuss the application of regression analysis in business decision making. Give examples on how the regression analysis can be used in business.

4. Do the following M (a) derive the Fourier transform of f (m) = 8 2, where a is a positive constant. (b) derive the Fourier transform of 35'2\". Hint: Recall that 1-? the lecture we derived the Fourier transform of the Gaussian function f (as) = e"a by the following steps. First, we computed the improper integral no I = f 3\""\"2 do: by squaring the integral and then using the polar coordinate to 00 53 evaluate the double integral. We then solved the ODE y' = y. (ii) Use R to simulate each of the processes in R and estimate the parameters and compare them with actual parameters in your models. Check the time series plot and acf plots for each process and examine each model carefully and report your observations. (1) {1 0.53 + .0632)Xf = (1 B}Zt. (ii) {1 0.2393111 = 2:. (iii) (1 0.03532JL = Z: 0.73:4. on a 7 -point Likert scale. A researcher investigates if the level of testosterone influences the level of risk taking behaviour among adolescents Risktaking behaviour is measured This is an example of: O Univariate statistics with testosterone as independent variable O Bivariate statistics with testosterone as independent variable O Univariate statistics with testosterone as depend Quiz Took O Bivariate statistics with testosterone as dependent variable